Transformer-Based Joint Learning Approach For Text Normalization In Vietnamese Automatic Speech Recognition Systems,
2024
Singapore Management University
Transformer-Based Joint Learning Approach For Text Normalization In Vietnamese Automatic Speech Recognition Systems, The Viet Bui, Tho Chi Luong, Oanh Thi Tran
Research Collection School Of Computing and Information Systems
In this article, we investigate the task of normalizing transcribed texts in Vietnamese Automatic Speech Recognition (ASR) systems in order to improve user readability and the performance of downstream tasks. This task usually consists of two main sub-tasks: predicting and inserting punctuation (i.e., period, comma); and detecting and standardizing named entities (i.e., numbers, person names) from spoken forms to their appropriate written forms. To achieve these goals, we introduce a complete corpus including of 87,700 sentences and investigate conditional joint learning approaches which globally optimize two sub-tasks simultaneously. The experimental results are quite promising. Overall, the proposed architecture outperformed the …
Latent Representation Learning For Geospatial Entities,
2024
Singapore Management University
Latent Representation Learning For Geospatial Entities, Ween Jiann Lee, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Representation learning has been instrumental in the success of machine learning, offering compact and performant data representations for diverse downstream tasks. In the spatial domain, it has been pivotal in extracting latent patterns from various data types, including points, polylines, polygons, and networked structures. However, existing approaches often fall short of explicitly capturing both semantic and spatial information, relying on proxies and synthetic features. This article presents GeoNN, a novel graph neural network-based model designed to learn spatially-aware embeddings for geospatial entities. GeoNN leverages edge features generated from geodesic functions, dynamically selecting relevant features based on relative locations. It introduces …
Data Provenance Via Differential Auditing,
2024
Peng Cheng Laboratory
Data Provenance Via Differential Auditing, Xin Mu, Ming Pang, Feida Zhu
Research Collection School Of Computing and Information Systems
With the rising awareness of data assets, data governance, which is to understand where data comes from, how it is collected, and how it is used, has been assuming evergrowing importance. One critical component of data governance gaining increasing attention is auditing machine learning models to determine if specific data has been used for training. Existing auditing techniques, like shadow auditing methods, have shown feasibility under specific conditions such as having access to label information and knowledge of training protocols. However, these conditions are often not met in most real-world applications. In this paper, we introduce a practical framework for …
Research On Simulation Resource Management Based On Graph Association Organization,
2024
Beijing Simulation Center, Beijing 100854, China
Research On Simulation Resource Management Based On Graph Association Organization, Zewei Liu, Yishan Ding, Tingyu Lin, Mingxing Ke, Liqing Guo, Yingying Xiao, Zhilong Zhao, Yan Li, Xuan Lü
Journal of System Simulation
Abstract: The simulation test and evaluation of intelligent system of systems, systems and single equipment is a complex system engineering, which requires effective management of multi-source, heterogeneous and distributed massive simulation resources scattered in cloud test centers and test sites of various units; and good control of dynamically generated tasks, assumptions, configurations, results, evaluations and other data and files. The traditional way of managing and querying simulation resources by category is inefficient and difficult to meet the requirements of large-scale intelligent simulation test and evaluation activities. An overall framework for simulation resource management based on graph association organization, defines a …
Simulation Study Of Personnel Evacuation In Fire Scenarios Of Old School Buildings,
2024
Institute of Earthquake Protection and Disaster Mitigation, Lanzhou University of Technology, Lanzhou 730050, China
Simulation Study Of Personnel Evacuation In Fire Scenarios Of Old School Buildings, Qiankun Zhu, Jiwu Li, Yongfeng Du
Journal of System Simulation
Abstract: In order to improve the emergency evacuation capability of an old school building under fire scenarios, a fire evacuation model of an old school building is developed. The PyroSim software is used to build a fire dispersion model to simulate and analyse the changes of smoke visibility, temperature and CO at the safety exit of the fire floor in the school building under the condition of mechanical smoke exhaust, automatic sprinkler and whether the windows of the fire room are open or not. The simulation of the exit status and evacuation of people has been carried out in conjunction …
A New Model Predictive Current Controller Forac-Dc Matrix Converter In Unbalanced Grids,
2024
School of Automation and Electronic Information, Xiangtan University, Xiangtan 411105, China
A New Model Predictive Current Controller Forac-Dc Matrix Converter In Unbalanced Grids, Wenlang Deng, Minghai Wu, Haipeng Xie, Yingjie Hu
Journal of System Simulation
Abstract: To reduce the fluctuation of active power on the grid side of AC-DC matrix converters under unbalanced input conditions and to address the issue of variable switching frequency in discrete model predictive control, this paper proposes a novel model predictive control method. This method selects effective vectors based on the phase angle of the grid current, thus avoiding the computational burden of evaluating the value function in traditional model predictive control. Additionally, a second-order extended complex Kalman filter is introduced, which achieves the computation accuracy of the secondorder term of the Taylor series expansion and enables the application of …
Path Planning Based On Improved A* And Dynamic Window Approach,
2024
School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, China
Path Planning Based On Improved A* And Dynamic Window Approach, Peng Ji, Xinyuan Zhang, Shuaixuan Gao, Shuorang Wei
Journal of System Simulation
Abstract: In response to the low efficiency, redundant turning points, and collision issues of the traditional A* algorithm, a smart vehicle path planning algorithm that integrates an improved A* algorithm with a dynamic window approach has been proposed. The algorithm has enhanced the search point selection method, optimized the evaluation function, selected key turning points based on the slope values between turning points, and removed redundant turning points. Between every two optimized key turning points, a dynamic window approach that balances speed and safety is used for local obstacle avoidance. Experiments show that compared to the traditional A* algorithm, this …
Research On System-Of-Systems Confrontation Simulation Method Based On Operation Loops,
2024
The 1st Research Department, 28th Research Institute of China Electronics Technology Corporation, Nanjing 210001, China
Research On System-Of-Systems Confrontation Simulation Method Based On Operation Loops, Shan Zhong, Yesheng Zhu, Menglu Zhou
Journal of System Simulation
Abstract: In the field of modeling and analyzing capabilities for operation system-of-systems (SoS), traditional structured capability assessment models lack the analysis of the interaction between both rivals and armies in different roles. The system model based on operation loop theory can be combined with the relationship between sensor, decision-making, influence, and target nodes for system capability calculation, but the existing model is usually only suitable for static analysis and cannot be used for dynamic simulation of SoS confrontation. In order to solve the problems above, a SoS confrontation simulation method based on operation loops is proposed. It abstracts both rivals’ …
Carbon Footprint Analysis And Low-Carbon Optimization Method Simulation Study Of Power Transformer Based On Digital Twin Technology,
2024
Economic and Technical Research Institute of State Grid Liaoning Electric Power Co., Ltd., Shenyang 110870, China
Carbon Footprint Analysis And Low-Carbon Optimization Method Simulation Study Of Power Transformer Based On Digital Twin Technology, Dongxue Li, Yan Liu, Boyao Shen, Yongteng Jing, Qiang Ma, Ran Liu
Journal of System Simulation
Abstract: Power transformers are the main energy-consuming equipment for substations. According to the goal of “carbon peak, carbon neutralization” in China, it is of great significance to accurately calculate the carbon footprint of transformers and seek low-carbon optimization methods. A method for constructing a digital twin model of power transformer magnetic characteristics is proposed. Based on the three-dimensional electromagnetic time-harmonic field finite element analysis method, a threedimensional model of SZ11-31.5MVA/66kV power transformer is established. The transformer loss map is obtained under fluctuating load condition, and the transformer digital twin model is constructed. The carbon footprint of the transformer is analyzed, …
Indicator Transfer Learning Based On Cloud Model And Maximum Mean Discrepancy,
2024
National Innovation Institute of Defense Technology, Academy of Military Science, Beijing 100071, China
Indicator Transfer Learning Based On Cloud Model And Maximum Mean Discrepancy, Lixia Xu, Jilong Zhong, Shaoshi Wu, Yishan Ding, Xiaoyu Zhai, Shizhao Chen, Yizhe Wang, Xue Wen, Juanfang Zeng, Xinwen Hou
Journal of System Simulation
Abstract: In response to the problem of rare data samples in application experiment scenarios, this paper proposes an indicator transfer learning method based on cloud models and Maximum Mean Discrepancy (MMD), which transfers the indicator calculation model from typical simulation experiment scenarios to application experiment scenarios to meet the needs across platform and domain simulation evaluation. Using the maximum mean difference method to align the indicator distribution in the typical simulation experiment scenario to the indicator distribution in the application experiment scenario, thereby achieves indicator transfer, and by using cloud models based on a small number of examples for modeling …
Research On Orb-Slam Algorithm Based On Windowed Matching Estimation,
2024
Department of Automation, North China Electric Power University (Baoding), Baoding 071003, China
Research On Orb-Slam Algorithm Based On Windowed Matching Estimation, Wanye Yao, Zewei Pang, Peijie Sun, Zhu Wang
Journal of System Simulation
Abstract: To address unstability of location accuracy of ORB-SLAM system caused by randomness of camera pose solution method, an improved pose solution method based on feature point windowed matching and analytical ICP is proposed, and the mobile robot ORB-SLAM system is constructed. The extracted feature points are windowed to improve matching efficiency while ensuring good feature point matching, the analytical ICP algorithm is used to solve the camera pose for avoiding iteration, and the windowed pose solution with the smallest error is selected for bundle adjustment to reduce the pose errors caused by local information loss or mismatching. The results …
Research On Digital Twin System Of Rockshaft Hoist,
2024
Institute of Electrical & Information Engineering, Anhui University of Science and Technology, Huainan 232001, China
Research On Digital Twin System Of Rockshaft Hoist, Baiting Zhao, Jianguo Shi, Xiaofen Jia
Journal of System Simulation
Abstract: In order to solve the problem of low intelligence and digitization of the current mine hoisting system, a method based on DT for digital modeling, 3D visualization, and virtual real interaction of shaft hoisting machines is proposed. Aiming at the rockshaft hoist system, based on the digital twin five dimensional model framework, we analyze the operating mechanism of the equipment, and model the fully physical digital system of the rockshaft hoist. By constructing multidimensional multi-scale models and multidimensional heterogeneous data models, twin digital scenes are constructed, and virtual real mapping technology is combined to achieve dynamic mapping and virtual …
A Multimodal Residual Spatial-Temporal Fusion Model Based On Automatic Sleep Classification,
2024
School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China; School of Electronics and Information Engineering, Wuxi University, Wuxi 214105, China
A Multimodal Residual Spatial-Temporal Fusion Model Based On Automatic Sleep Classification, Yecai Guo, Shuang Tong
Journal of System Simulation
Abstract: Highly accurate sleep staging plays a crucial role in correctly assessing sleep conditions. Aiming at the problem that the existing convolutional network cannot obtain the topological characteristics of physiological signals, a sleep staging algorithm based on multi-modal residual spatio-temporal fusion is proposed. Time-frequency images and spatio-temporal images are obtained using short-time Fourier transform and adaptive map convolution, which are converted into high-dimensional feature vectors; lightweight interaction of feature information flow is realized through time-frequency feature and spatiotemporal feature extraction modules; the feature enhancement fusion module fuses feature information to outputs sleep staging results. The results show that the model …
An Improved Path Planning Algorithm For Mobile Robots,
2024
Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China; Key Laboratory of Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming 650500, China
An Improved Path Planning Algorithm For Mobile Robots, Haijie Sun, Hongjun San, Le Xiao, Dexin Yao, Jiupeng Chen, Xiaoyuan Yang
Journal of System Simulation
Abstract: To solve the problems of invalid sampling and non-optimal paths of the RRT, the quasi-stream avoidance algorithm is proposed. The RRT algorithm is introduced to specify the sampling interval to limit the sampling points and enhance the goal-oriented nature of sampling. The quasi-stream avoidance algorithm incorporating the A* algorithm (QSA*) is used to quickly bypass the obstacle when it is encountered. A path optimization algorithm is used to smooth the searched path. The simulation results show that compared with the RRT algorithm, the computation time of the RRT-QSA* algorithm is reduced by 96.83%~99.88%, the number of search nodes is …
Research On Autonomous Decision-Making In Air-Combat Based On Improved Proximal Policy Optimization,
2024
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Research On Autonomous Decision-Making In Air-Combat Based On Improved Proximal Policy Optimization, Dianwei Qian, Hongmin Qi, Zhen Liu, Zhiming Zho, Jianqiang Yi
Journal of System Simulation
Abstract: To address the problems of high information redundancy and slow convergence speed of traditional reinforcement learning in air-combat autonomous decision-making applications, a proximal policy optimization air-combat autonomous decision-making method, based on dual observation and composite reward is proposed. A dual observation space, which contains interaction information as the main information and individual feature information as a supplement, was designed to reduce the influence of redundant battlefield information on the training efficiency of the decision model. A composite reward function combining result reward and process reward was designed to improve convergence speed. The generalized advantage estimator was applied in the …
An Intelligent Adversaries Behavior Simulation Technology Based On Improved Behavior Trees,
2024
Information System Engineering National Important Laboratory, the 28th Research Institute of China Electronics Technology Group Corporation, Nanjing 210007, China
An Intelligent Adversaries Behavior Simulation Technology Based On Improved Behavior Trees, Fang Zhou, Bo Fan, Xiaoyi Liu, Yishan Ding, Ningxin Zhang, Yachao Shao, Xiaoyu Zhai
Journal of System Simulation
Abstract: Intelligent algorithm/intelligent platform/intelligent system intelligence capability testing and evaluation need to solve high-level intelligent opponent simulation problems, an intelligent opponent behavior simulation technology based on improved behavior tree is proposed. Four types of behavior tress nodes are designed, including behavior control, combat tasks, behavior actions, and execution condition node. Five atomic behavior actions and parameters are established, including maneuver, reconnaissance and early warning, command and decision-making, firepower strike, and electronic interference node. Five atomic condition nodes are provided, including target selection, weapon launch, and incoming weapon judgment node. The intelligent adversarial behavior simulation system is designed, including a behavior …
Adversarial Simulation Testing Algorithm For Svm Based On Multi-Objective Evolutionary Optimization,
2024
Chinese Flight Test Establishment, Xi'an 710089, China
Adversarial Simulation Testing Algorithm For Svm Based On Multi-Objective Evolutionary Optimization, Feixing Li, Lining Xing, Yu Zhou
Journal of System Simulation
Abstract: Machine learning typically mines underlying patterns and rules from data, making it susceptible to phenomena such as overfitting and underfitting, which in turn affects the generalization and robustness of learning models. This paper explores the potential fragility and instability of SVM from the perspective of adversarial simulation testing. The adversarial simulation strategy employed involves selectively contaminating training sample labels to simulate an attack on the SVM classifier, thereby degrading its performance and testing its dependency on training samples. To explore the ceiling of performance degradation of an SVM classifier under the combination attack of different samples, the contradictory objectives …
Uav Online Track Planning Based On Dmoea-Aptc Algorithm,
2024
College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
Uav Online Track Planning Based On Dmoea-Aptc Algorithm, Erchao Li, Shenghui Zhang
Journal of System Simulation
Abstract: In order to solve the dynamic multi-objective optimization problem with time correlation, this paper introduces the concept of time correlation feature and establishes the model of UAV timecorrelation dynamic multi-objective optimization problem moedl on the basis of UAV online track planning problem, and proposes a dynamic multi-objective double-layer optimization algorithm using adaptive predictive response mechanism and time-correlation optimization mechanism (DMOEA-APTC). The intensity of environmental change was judged according to the correlation of environmental change and different response mechanisms were used to quickly adapt to environmental change. In the optimization process, the least square method was used to learn the …
Edge Surveillance Task Offloading And Resource Allocation Algorithm Based On Drl,
2024
School of Computer Science, Hubei University of Technology, Wuhan 430000, China
Edge Surveillance Task Offloading And Resource Allocation Algorithm Based On Drl, Chao Li, Jiabao Li, Caichang Ding, Zhiwei Ye, Fangwei Zuo
Journal of System Simulation
Abstract: For the resource limitation of intensive surveillance tasks in edge computing, a surveillance task offloading and resource allocation algorithm based on DRL is proposed. With the optimization objectives of surveillance task delay and recognition accuracy, the joint decision objective optimization solution of task offloading, wireless channel allocation, and image compression rate was modeled as a Markov decision process. To address the problem of slow and unstable algorithm convergence due to the high volatility of training samples caused by the dynamic nature of wireless channels and the randomness of surveillance tasks, an attention mechanism is used to jointly encode channel …
Study On Invulnerability Of Urban Rail Network Considering Sum Of The Neighbors Degree,
2024
School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Study On Invulnerability Of Urban Rail Network Considering Sum Of The Neighbors Degree, Shuqing Li, Yixiao Song, Guojian Zhong
Journal of System Simulation
Abstract: In order to solve the problem of network cascade paralysis caused by urban rail station or line failure, considering the influence of the first-order neighborhood of network nodes, the load distribution impedance coefficient is proposed based on the nonlinear capacity load model, and a nonlinear capacity load optimization model considering the sum of the neighbors degree is constructed. By optimizing load structure, the alternative probability of nodes during load redistribution is adjusted to reduce the number of node failures in the cascading process, thereby the rail network invulnerability is improved. Taking Chongqing rail network as an example, the rail …
